Abstract
From the perspective of factor input in the production process, this paper puts forward the issue of accounting and capitalization of generalized data output, brings the output of data reprocessing into the scope of statistical accounting, and proposes a systematic evolution chain of data factor forms and the division method of data factor value composition and sources. Then, based on the GDP accounting platform, a three-in-one theoretical framework covering “output-investment-assets” is built for capitalization accounting of data factor, and an accounting path covering “cost → input → output → capital formation → data assets” is designed to improve and highlight the cost accounting method with “value appreciation” as the core. Taking China as an example, its data capital formation and asset size are measured by matching data-intensive industries with data professionals, and by synthesizing data from multiple sources. The rationality and self-consistency of the theoretical and methodological research is verified by the empirical results. This study can provide theoretical reference for bringing the value accounting of data factor into the basic framework of the Systems of National Accounts (SNA). Moreover, its empirical research paradigm can also provide reference for relevant countries to carry out capitalization accounting for data factor (CADF).
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